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This study investigates the role of agricultural landuse change in the observed increase in extreme precipitation during the 20 century. Landuse input was constructed for the Community Land Model in the WRF-ARW using county-level planting data from the USDA for two periods: the 1940s and 2010. Crops were separated into small grains, winter wheat, soybean, and maize. When simulations are run using these two land datasets for the 1949-2010 period, the 2010 landuse has higher frequencies of extreme precipitation above 24-26 mm day or 1 in day. This indicates that cropland shifts in the 20 century when society shifted from large oat cultivation to feed work animals on traditional farms to soybean and maize following the industrial revolution have contributed to increases in extreme precipitation across the central U.S. Additionally, this study makes simple changes to convective parameterizations to allow grid-scale microphysics to have a larger role in producing precipitation with the goal of improving MCC production. Using an objective MCC detection algorithm that uses only the precipitation field, no scheme is presented as the best performer, although modifications we made performed on par with unmodified schemes. We also examined MCC production and trends in the Can-RCM4, CRCM5, HIRHAM, and RCA4 models under the CORDEX framework. Although trends were found within each model, variation was large among models; this reinforces the importance of considering variability in regional climate modeling when analyzing or forecasting hydrologic trends.

Mesoscale convective complexes in regional climate modeling and increased extreme precipitation due to agricultural landuse change over the central U.S.